Differential cognitive responses to guqin music and piano music in Chinese subjects: an event-related potential study

目的 研究古琴(一种古老的中国乐器)和钢琴音乐对认知的影响.方法 记录和分析了中国被试在两种音乐背景(古琴音乐,钢琴音乐)下完成听觉oddball任务的行为和事件相关电位(event-related potential,ERP)数据.结果 中国被试在本土文化的音乐环境(古琴音乐)下,前额区诱导出更大的P300,这一结果和已有的相关研究是相符的.同时,不同音乐背景对ERP产生的影响在N1和LPC(包括P300和P500)上也表现出差别:中国被试在古琴音乐背景下比钢琴音乐背景下表现出更多的右前侧颞叶的参与.结论 因为古琴音乐的五声调式和汉语发音的音调具有对应关系,因此我们推断在古琴音乐下所表现出的这种特性与被试的汉语环境有关.

Crossmodal effects of Guqin and piano music on selective attention: An event-related potential study

To compare the effects of music from different cultural environments (Guqin: Chinese music; piano: Western music) on crossmodal selective attention, behavioral and event-related potential (ERP) data in a standard two-stimulus visual oddball task were reco

Crossmodal effects of Guqin and piano music on selective attention: An event-related potential study (vol 466, pg 21, 2009)

Special thanks to Christopher Blair and Mumtaz Baig for their suggestions. This work was supported by National Basic Research Program of China (973 Program, 2007CB411600), National Natural Science Foundation of China (30621092), and Bureau of Science and Technology of Yunnan Province.

Non-goal scene analysis for soccer video

The broadcast soccer video is usually recorded by one main camera, which is constantly gazing somewhere of playfield where a highlight event is happening. So the camera parameters and their variety have close relationship with semantic information of soccer video, and much interest has been caught in camera calibration for soccer video. The previous calibration methods either deal with goal scene, or have strict calibration conditions and high complexity. So, it does not properly handle the non-goal scene such as midfield or center-forward scene. In this paper, based on a new soccer field model, a field symbol extraction algorithm is proposed to extract the calibration information. Then a two-stage calibration approach is developed which can calibrate camera not only for goal scene but also for non-goal scene. The preliminary experimental results demonstrate its robustness and accuracy. (c) 2010 Elsevier B.V. All rights reserved.

Biologically Inspired Features for Scene Classification in Video Surveillance

Inspired by human visual cognition mechanism, this paper first presents a scene classification method based on an improved standard model feature. Compared with state-of-the-art efforts in scene classification, the newly proposed method is more robust, more selective, and of lower complexity. These advantages are demonstrated by two sets of experiments on both our own database and standard public ones. Furthermore, occlusion and disorder problems in scene classification in video surveillance are also first studied in this paper.